Citations (28)
Keep up to date with the latest research on this topic with citation updates for this article.
Read on this site (8)
Sören R. Künzel, Theo F. Saarinen, Edward W. Liu & Jasjeet S. Sekhon. (2022) Linear Aggregation in Tree-Based Estimators. Journal of Computational and Graphical Statistics 31:3, pages 917-934.
Read now
Read now
Chenglong Ye, Yi Yang & Yuhong Yang. (2018) Sparsity Oriented Importance Learning for High-Dimensional Linear Regression. Journal of the American Statistical Association 113:524, pages 1797-1812.
Read now
Read now
Tianhao Wang & Yingcun Xia. (2014) A Piecewise Single-Index Model for Dimension Reduction. Technometrics 56:3, pages 312-324.
Read now
Read now
Philip Dewe & Linda Trenberth. (2012) Exploring the relationships between appraisals of stressful encounters and the associated emotions in a work setting. Work & Stress 26:2, pages 161-174.
Read now
Read now
Linda Trenberth & Philip Dewe. (2006) Understanding the experience of stressors: The use of sequential analysis for exploring the patterns between various work stressors and strain. Work & Stress 20:3, pages 191-209.
Read now
Read now
Philip Dewe & Linda Trenberth. (2005) An exploration of the role of leisure in coping with work related stress using sequential tree analysis. British Journal of Guidance & Counselling 33:1, pages 101-116.
Read now
Read now
S. Magnussen, P. Boudewyn & M. Wulder. (2004) Contextual classification of Landsat TM images to forest inventory cover types
. International Journal of Remote Sensing 25:12, pages 2421-2440.
Read now
Read now
Linda Trenberth & Philip Dewe. (2002) The importance of leisure as a means of coping with work related stress: An exploratory study. Counselling Psychology Quarterly 15:1, pages 59-72.
Read now
Read now
Articles from other publishers (20)
Marvin Schone & Martin Kohlhase. (2021) Curvature-Oriented Splitting for Multivariate Model Trees. Curvature-Oriented Splitting for Multivariate Model Trees.
Zhenghui Feng, Lu Lin, Ruoqing Zhu & Lixing Zhu. (2019) Nonparametric variable selection and its application to additive models. Annals of the Institute of Statistical Mathematics 72:3, pages 827-854.
Crossref
Crossref
Khadija El Bouchefry & Rafael S. de Souza. 2020. Knowledge Discovery in Big Data from Astronomy and Earth Observation. Knowledge Discovery in Big Data from Astronomy and Earth Observation
225
249
.
Marvin Schöne & Martin Kohlhase. 2020. Intelligent Data Engineering and Automated Learning – IDEAL 2020. Intelligent Data Engineering and Automated Learning – IDEAL 2020
41
50
.
Craig A. Rolling, Yuhong Yang & Dagmar Velez. (2018) COMBINING ESTIMATES OF CONDITIONAL TREATMENT EFFECTS. Econometric Theory 35:6, pages 1089-1110.
Crossref
Crossref
Jicai Liu, Peirong Xu & Heng Lian. (2019) Estimation for single-index models via martingale difference divergence. Computational Statistics & Data Analysis 137, pages 271-284.
Crossref
Crossref
Hongfan Zhang. (2018) Quasi-likelihood estimation of the single index conditional variance model. Computational Statistics & Data Analysis 128, pages 58-72.
Crossref
Crossref
Luı́s Torgo. 2017. Encyclopedia of Machine Learning and Data Mining. Encyclopedia of Machine Learning and Data Mining
1080
1083
.
Dan Maljovec, Bei Wang, Paul Rosen, Andrea Alfonsi, Giovanni Pastore, Cristian Rabiti & Valerio Pascucci. (2016) Rethinking sensitivity analysis of nuclear simulations with topology. Rethinking sensitivity analysis of nuclear simulations with topology.
Luı́s Torgo. 2016. Encyclopedia of Machine Learning and Data Mining. Encyclopedia of Machine Learning and Data Mining
1
4
.
Taiji Suzuki & Masashi Sugiyama. (2013) Sufficient Dimension Reduction via Squared-Loss Mutual Information Estimation. Neural Computation 25:3, pages 725-758.
Crossref
Crossref
Paul K. Amalaman, Christoph F. Eick & Nouhad Rizk. 2013. Machine Learning and Data Mining in Pattern Recognition. Machine Learning and Data Mining in Pattern Recognition
325
339
.
Marcin Czajkowski & Marek Kretowski. 2013. Artificial Intelligence and Soft Computing. Artificial Intelligence and Soft Computing
1
11
.
Alexei Bocharov & Bo Thiesson. 2013. Pattern Recognition - Applications and Methods. Pattern Recognition - Applications and Methods
93
107
.
Anca Maria Ivanescu, Thivaharan Albin, Dirk Abel & Thomas Seidl. (2012) Employing the Principal Hessian Direction for Building Hinging Hyperplane Models. Employing the Principal Hessian Direction for Building Hinging Hyperplane Models.
Qin Wang & Weixin Yao. (2012) An adaptive estimation of MAVE. Journal of Multivariate Analysis 104:1, pages 88-100.
Crossref
Crossref
David S. Vogel, Ognian Asparouhov & Tobias Scheffer. (2007) Scalable look-ahead linear regression trees. Scalable look-ahead linear regression trees.
Isabel Nepomuceno-Chamorro, Jesús S. Aguilar–Ruiz, Norberto Díaz–Díaz, Domingo S. Rodríguez–Baena & Jorge García. 2007. Intelligent Data Engineering and Automated Learning - IDEAL 2007. Intelligent Data Engineering and Automated Learning - IDEAL 2007
850
859
.
Duncan Potts & Claude Sammut. (2005) Incremental Learning of Linear Model Trees. Machine Learning 61:1-3, pages 5-48.
Crossref
Crossref
Lue Heng-Hui. (2019) A study of sensitivity analysis on the method of Principal Hessian Directions. Computational Statistics 16:1, pages 109-130.
Crossref
Crossref